Title :
Unsupervised change detection with very high-resolution SAR images by multiscale analysis and Markov random fields
Author :
Moser, Gabriele ; Serpico, Sebastiano B.
Author_Institution :
Dept. of Biophys. & Electron. Eng., Univ. of Genoa, Genoa, Italy
Abstract :
Change detection represents an important tool in environmental monitoring and disaster management. Here, a novel unsupervised change-detection method is proposed for very high-resolution SAR images, by integrating wavelet multiscale feature extraction, Markov random fields for contextual modeling, and generalized Gaussian models. Experiments with COSMO-SkyMed data remark the effectiveness of the method as compared with previous methods.
Keywords :
Gaussian processes; Markov processes; environmental factors; feature extraction; monitoring; radar imaging; synthetic aperture radar; COSMO-SkyMed; Markov random fields; disaster management; environmental monitoring; generalized Gaussian models; high-resolution SAR images; multiscale analysis; multiscale feature extraction; unsupervised change detection; Accuracy; Discrete wavelet transforms; Ice; Markov processes; Pixel; Remote sensing; Speckle; Markov random fields; Unsupervised change detection; generalized Gaussian distribution; very-high resolution synthetic aperture radar; wavelets;
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2010 IEEE International
Conference_Location :
Honolulu, HI
Print_ISBN :
978-1-4244-9565-8
Electronic_ISBN :
2153-6996
DOI :
10.1109/IGARSS.2010.5652435
